Emerging and future wireless systems require ever increasing efficiency in the utilization of the radio frequency spectrum in order to increase the data rate achievable within a given transmission bandwidth. Increases in the throughput achievable per unit bandwidth can be accomplished by employing multiple transmit and receive antennas combined with signal processing. Indeed, a number of recently developed techniques and emerging standards are based on employing multiple antennas at a base station to improve the reliability of data communication over wireless media without compromising the effective data rate of the wireless systems. Alternatively, the multiple antennas can be used to increase the data rates achievable per unit bandwidth.
Specifically, recent advances in wireless communications have demonstrated that by jointly encoding symbols over time and space (e.g., using multiple transmit antennas at a base station) one can obtain reliability (diversity) benefits as well as increases in the effective data rate from the base station to each cellular user. These multiplexing (throughput) gains and diversity benefits are inherently dependent on the number of transmit and receive antennas in the system being deployed, in the sense that they are fundamentally limited by the multiplexing-diversity trade-offs curves that are dictated by the number of transmit and the number of receive antennas in the system. Very high-rate designs have been demonstrated that achieve very high spectral efficiencies by exploiting large numbers of transmit and receive antennas. Such MIMO schemes form the basis of what are referred to as single-user MIMO systems. According to these schemes, channels corresponding to a distinct set of time-frequency slots are used to send multiple streams to a single user by coding an information bearing stream into a signal that is transmitted over the multiple antennas on the allocated channel. A scheduler is then used to schedule the transmissions for different users on different channels, in a similar way that it is done in a SISO transmission.
Recently, it was demonstrated that very high sum-rates (i.e., the sum of the rates of the users who are being transmitted to) can be obtained with simple mobiles employing one or two antennas, provided that several transmit antennas are available at the base-station, and all the transmit-receive channels are known to the transmitting base station. These techniques are referred to as Multi-User MIMO (MU-MIMO) schemes. The achievable rates by these schemes in general strongly depend on the quality of the channel estimates available at the base station. One of the simplest classes of multiuser MIMO precoders, known as zero-forcing (or block zero-forcing) MU-MIMO precoders, use knowledge of all the channels between transmit/receive antenna pairs in order to linearly precode the users' signals that are to be transmitted, so that the receiver of each user “sees” its own signal in noise.
Existing multicell deployments are known to provide uneven throughputs to different users, with users at the edge of each cell suffering in throughput with respect to users in the center of the cell. A number of schemes have been proposed for multicell deployments using MIMO transmission. Some multicell deployments employ isolated-cell joint scheduling/MIMO preceding algorithms without coordination across cells. Coordination is limited to the antennas within each cell. Also while these schemes are readily scalable, they are limited by interference (coming from antennas located outside the cell) and suffer greatly in edge throughput. Some fully coordinated multicell deployments are not interference-limited and can provide arbitrarily high sum-throughput (with increased power) and arbitrarily high edge throughput. However, they are not scalable as all transmit antennas across all cells need to be coordinated. Also the complexity grows very fast with the number of antennas in the whole network and the number of users that need to be scheduled, and quickly becomes impractical. Therefore, the scheme provides an upper bound on the performance of any practical scheme.
The current evolution of the 3G standard, termed Long-Term Evolution (LTE), proposes an inter-cell interference coordination technique whereby the power levels of different channels are adjusted differently in adjacent cells. As a result, the interference seen by edge users is reduced and higher data rates can be achieved. LTE assumes a Single-User MIMO (SU-MIMO) transmission in the downlink and within each cell. In addition, base stations (or controllers) always control the same set of antennas, the power levels across channels remain unchanged over time and the same set of users for scheduling.